摘要
在信任计算中,推荐信任具有极强的主观性,存在欺骗、诋毁等攻击行为,这些将掩盖被推荐用户行为的真实性,威胁系统安全。针对该问题,提出一种基于用户行为的加权信任计算方法,使用时间衰减标识反馈信息的时间属性,通过直接信任和推荐信任加权计算用户信任度;同时采用反馈可信度评估第三方推荐信任的真实性。仿真实验表明该方法具有较好的动态适应性,能够有效平衡恶意推荐,准确反映用户的行为变化,并计算用户行为的可信性,为系统安全决策提供可靠支持。
In trust computation,recommendation trust has very strong subjectivity and some aggressive behaviors like deception and slander.Those factors will conceal the authenticity of the behaviors of recommended users and threaten the system security.To address the problem,this paper proposed a weighted trust computation method based on users＇ behaviors.The time attribute of feedback information was identified by using time attenuation.And the trustworthiness of users was computed based on direct trust and recommendation trust with different weights.Also,this paper introduced feedback credibility to evaluate the authenticity of recommendation trust.The simulation experiments show that this method has better adaptability to the dynamics of trust.It can effectively reduce the impact of malicious recommended trust,and compute accurately the trust of users according to users＇ behaviors,which provides reliable information to correctly make security decision for the system.
出处
《计算机应用》
CSCD
北大核心
2011年第7期1887-1890,共4页
journal of Computer Applications
基金
广西教育厅基金资助项目(201010LX156)
广西研究生教育创新计划项目(2010105950810M18)
桂林电子科技大学博士启动基金资助项目(UF10020Y)
关键词
直接信任
推荐信任
时间衰减
反馈可信度
direct trust
recommendation trust
time attenuation
feedback credibility
